Top Machine Learning Jobs in Tallahassee, FL

The Global Head of Solutions Engineering leads a team, ensuring technical excellence and customer success in pre-sales and onboarding while driving team development and cross-functional partnerships.

The Director of Product Management will lead a team to manage CAMP's Aircraft Health Management platform, driving product strategy, modernization, and execution with a focus on customer outcomes and market innovation.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Work on-site with portfolio companies to design, prototype, and deliver full-stack digital and AI solutions. Lead discovery, deployment, and post-launch iteration, ensure security/compliance, resolve technical issues, mentor teams, and drive enterprise integrations and adoption. Frequent domestic travel and stakeholder management required.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

Lead enterprise sales for Hippocratic AI to commercial-stage biotech accounts. Manage end-to-end deals, build ROI business cases, maintain pipeline and forecasting, partner with Product/Clinical/ML teams, and represent the company at industry events to drive growth and large strategic contracts.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

The DS&ML Group Product Manager oversees Data Science and Machine Learning capabilities, defining strategic vision, managing product portfolios, and ensuring delivery aligned with business needs. Responsibilities include developing roadmaps, executing models, scaling functionalities, and mentoring a team.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

Lead strategy and execution for MarketScan data products and delivery experiences. Define portfolio vision, prioritize data product innovation and operational excellence, drive cloud and AI enablement, ensure data quality/compliance, engage executives and customers, and build a high-performing product organization to grow adoption and revenue.

Design, build, and deploy novel sensor hardware and data acquisition systems; curate geoscientific datasets; develop statistical, physics-based, and ML models (2D/3D) to predict mineralization; create visualizations and evaluation tools; collaborate with geoscientists, engineers, and vendors; deploy sensors in the field and integrate results to guide exploration programs.

Lead end-to-end supply chain transformation engagements, advising executives and directing multidisciplinary teams to improve planning, procurement, logistics, inventory, and supplier performance. Design future-state architectures, build business cases, drive implementation, grow client relationships, and scale practice capabilities while delivering measurable operational and financial impact.

Lead end-to-end supply chain transformation engagements for commercial and utility clients. Advise executives, design future-state supply chain architectures, oversee implementation across planning, procurement, logistics, and analytics, build financial value cases, and manage multidisciplinary teams to deliver measurable operational and financial results.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

As a Software Engineer, you will design solutions, write quality code, collaborate with teams, and ensure efficient data delivery for client applications.

SoftSnow is seeking an AI Ethicist to define ethical guidelines, assess risks, and ensure compliance in AI implementations across various industries.

The Senior Principal Product Manager will lead Rockerbox's measurement and modeling products, ensuring accurate methodologies and partnering with Data Science and Engineering to drive product strategy and execution.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Lead vision, strategy, and roadmap for data products powering catalog, taxonomy, recommendations, ads, and AI/ML systems. Partner with data engineering to build data platform, governance, identifiers, and quality metrics. Ship data-driven experiences for retailers, partners, and internal teams and translate data quality into measurable business outcomes.

Provide technical advisory and solution feasibility analysis for enterprise AI initiatives. Evaluate AI engineering approaches, integration complexity, reusable components, and architectural tradeoffs. Support prototyping guidance, vendor capability evaluation, and surface governance, risk, and technical constraints to inform enterprise decisions.